An Alternative for PID control: Predictive Functional Control - A Tutorial

PFC (Predictive Function Control) can be considered as a bridge between PI(D) and complex MPC. PI(D) control can have problems handling dead time and constraints. PFC handles these cases and is often better than using a Smith predictor. PFC is a simple realizable MPC which thus uses prediction and preview of key variables. PFC can be implemented via simple program code and thus has cheap license costs. The tutorial introduces the basic idea of PFC and algorithms for typical processes. Simulations illustrate its effectiveness and advantages over PI(D) and Smith predictors

Jahresbericht 2016 / Institut für Angewandte Informatik (KIT Scientific Reports ; 7736)

Im Jahresbericht 2016 des Instituts für Angewandte Informatik werden, nach einem kurzen Überblick über die Arbeiten, die Forschungsergebnisse dieses Jahres vorgestellt. Die Einordnung erfolgt entsprechend der Zuordnung der Projekte zu den Helmholtz-Programmen SCI, EMR, RE, TIS, BIFTM, STN und SBD. Es schließt sich eine Verzeichnis der im Berichtszeitraum erschienen Publikationen des Instituts an

Sparsity Methods for Systems and Control

The method of sparsity has been attracting a lot of attention in the fields related not only to signal processing, machine learning, and statistics, but also systems and control. The method is known as compressed sensing, compressive sampling, sparse representation, or sparse modeling. More recently, the sparsity method has been applied to systems and control to design resource-aware control systems. This book gives a comprehensive guide to sparsity methods for systems and control, from standard sparsity methods in finite-dimensional vector spaces (Part I) to optimal control methods in infinite-dimensional function spaces (Part II). The primary objective of this book is to show how to use sparsity methods for several engineering problems. For this, the author provides MATLAB programs by which the reader can try sparsity methods for themselves. Readers will obtain a deep understanding of sparsity methods by running these MATLAB programs. Sparsity Methods for Systems and Control is suitable for graduate level university courses, though it should also be comprehendible to undergraduate students who have a basic knowledge of linear algebra and elementary calculus. Also, especially part II of the book should appeal to professional researchers and engineers who are interested in applying sparsity methods to systems and control

Entwicklungspfade intelligenter Transportsysteme für den Straßengüterverkehr

Today's road network has reached its limits in most major cities and at certain times. Similarly, the capacity of the road network is largely exhausted. In addition, the change in delivery cycles in the food industry from a regular delivery structure to just-in-time deliveries leads to an increased delivery volume. But also E-commerce, the share economy and the customer's demand for faster delivery (same-day delivery) are leading to an additional rise in the supply sector. With the road infrastructure remaining the same, it is therefore not surprising that more and more slow-moving traffic and congestion are occurring. Intelligent transport systems (ITS) offer the possibility to improve the road capacity without excessive structural measures. The aim of this dissertation project is to provide insights of research achieved so far in the field of ITS for road freight transport and to estimate further developments by means of scenario generation. In addition to the presentation of ITS for road freight transport and the creation of environmental scenarios, action implications for the individual areas of ITS in road freight transport are presented. If the first scenario occured, this would have many positive effects on the transport process, but it would be of little importance, as the favourable factors are present in this scenario. If the second scenario occured, this would have many effects and a medium significance for ITS. In the case of the third scenario, this would be of medium to high significance, since in this scenario there are few ITS factors favouring road freight transport. The effects on the intelligent transport sector would be correspondingly small because these systems would not exist. This work provides first future oriented analysis in ITS related research